A Smartphone-Integrated Ratiometric Fluorescence Sensor for the Ultrasensitive and Selective Detection of 5-Heneicosylresorcinol in Whole Wheat Foods.

Precise on-site monitoring of alkylresorcinols, a vital biomarker, is crucial for verifying whole wheat foods and accurately quantifying the whole wheat content in various consumer and industrial products. Herein, for the first time, we introduce a novel ratiometric fluorescence sensor (CDs@ZIF-8/CdTe@MIP) for ultrasensitive and selective detection of alkylresorcinols. 5-Heneicosylresorcinol (C21:0 AR), the primary alkylresorcinol homologue in whole wheat grains, was selected as the target analyte. This analyte was specifically and selectively recognized by the incorporation of a molecularly imprinted polymer (MIP) layer. Within this nanoreactor, blue-emitting carbon dots embedded in zeolitic imidazolate framework-8 (CDs@ZIF-8) and orange-emitting CdTe quantum dots served as the self-calibration signal and response signal, respectively. Exploiting a photoinduced electron transfer effect between CdTe and C21:0 AR, the established fluorescence sensor exhibited remarkable sensing performance, offering wide linear responses in 0.005-1 µg·mL-1 and 1-80 µg·mL-1 concentration ranges, and achieving a low detection limit of 1.14 ng·mL-1. The proposed assay effectively detected C21:0 AR in real samples, including 8 whole wheat foods and 19 whole wheat grains, demonstrating good recoveries and relative standard deviation. Furthermore, an intelligent sensing platform was established by integrating CDs@ZIF-8/CdTe@MIP with a smartphone-assisted device, thus validating the feasibility of visual and on-site monitoring of C21:0 AR. Because of its rapid response, portability, cost-effectiveness, superior sensitivity, and high selectivity, the proposed sensor serves as a reliable method for the analysis of C21:0 AR, thus having substantial potential for on-site monitoring of whole wheat foods.

A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention.

Deep learning-based denoising of low-dose medical CT images has received great attention both from academic researchers and physicians in recent years, and has shown important application value in clinical practice. In this work, a novel two-branch and multi-scale residual attention-based network for low-dose CT image denoising is proposed. It adopts a two-branch framework structure, to extract and fuse image features at shallow and deep levels respectively, to recover image texture and structure information as much as possible. We propose the adaptive dynamic convolution block (ADCB) in the local information extraction layer. It can effectively extract the detailed information of low-dose CT denoising and enables the network to better capture the local details and texture features of the image, thereby improving the denoising effect and image quality. Multi-scale edge enhancement attention block (MEAB) is proposed in the global information extraction layer, to perform feature fusion through dilated convolution and a multi-dimensional attention mechanism. A multi-scale residual convolution block (MRCB) is proposed to integrate feature information and improve the robustness and generalization of the network. To demonstrate the effectiveness of our method, extensive comparison experiments are conducted and the performances evaluated on two publicly available datasets. Our model achieves 29.3004 PSNR, 0.8659 SSIM, and 14.0284 RMSE on the AAPM-Mayo dataset. It is evaluated by adding four different noise levels σ = 15, 30, 45, and 60 on the Qin_LUNG_CT dataset and achieves the best results. Ablation studies show that the proposed ADCB, MEAB, and MRCB modules improve the denoising performances significantly. The source code is available at https://github.com/Ye111-cmd/LDMANet .

The trends of non-accidental mortality burden attributed to compound hot-dry events in China and its provinces in a global warming world.

BACKGROUND: Global warming has provoked more co-occurrence of hot extreme and dry extreme, namely compound hot-dry events (CHDEs). However, their health impacts have seldom been investigated. This study aimed to characterize CHDEs and assess its mortality burden in China from 1990 to 2100. METHODS: CHDEs were defined as a day when daily maximum temperature > its 90th percentile and Standardized Precipitation Index < its 50th percentile. A two-stage approach, including a distributed lag nonlinear model (DLNM) and a multivariate meta-analysis, was used to estimate exposure-response associations of CHDEs with mortality in 358 counties/districts during 2006-2017 in China, which was then applied to assess the national mortality burden attributable to CHDEs from 1990 to 2100. FINDINGS: We observed a significant increasing trend of CHDEs in China until mid-21st century, and then flatted, while the duration and intensity of CHDEs continuously increased across the 21st century. CHDEs were much riskier (ER=17.82 %, 95 %CI: 14.17 %-21.60 %) than independent hot events (ER=5.86 %,95 %CI: -0.04 %,12.45 %) or dry events (ER=0.07 %,95 %CI: -1.22 %, 1.38 %), and there was significantly additive interaction between hot events and dry events (AP=0.10,95 %CI: 0.04, 0.16). Females (ER=24.28 %, 95 %CI: 19.21 %-29.56 %), the elderly (ER=23.28 %, 95 %CI: 18.23 %-28.55 %), and people living in humid area (ER=18.98 %, 95 %CI: 15.08 %-23.02 %) had higher mortality risks than their counterparts. Mortality burden attributed to CHDEs significantly increased during historical observation and became stable since mid-21st century in China. INTERPRETATION: CHDEs would significantly increase mortality with higher risk for females, the elderly and people living in humid areas. Mortality burden has significantly increased during historical observation and will keep relatively steady since mid-21st century.

Single-sample gene set enrichment analysis reveals the clinical implications of immune-related genes in ovarian cancer.

Purpose: Ovarian cancer (OC) is a common gynecological malignancy with poor prognosis and substantial tumor heterogeneity. Due to the complex tumor immune microenvironment (TIME) among ovarian cancer, only a few patients have an immune response to immunotherapy. To investigate the differences in immune function and identify potential biomarkers in OC, we established a prognostic risk scoring model (PRSM) with differential expression of immune-related genes (IRGs) to identify critical prognostic IRG signatures. Methods: Single-sample gene set enrichment analysis (ssGSEA) was used to investigate the infiltration of various immune cells in 372 OC patients. Then, COX regression analysis and Lasso regression analysis were used to screen IRGs and construct PRSM. Next, the immunotherapy sensitivity of different risk groups regarding the immune checkpoint expression and tumor mutation burden was evaluated. Finally, a nomogram was created to guide the clinical evaluation of the patient prognosis. Results: In this study, 320 immune-related genes (IRGs) were identified, 13 of which were selectively incorporated into a Prognostic Risk Scoring Model (PRSM). This model revealed that the patients in the high-risk group were characterized as having poorer prognosis, lower expression of immune checkpoints, and decreased tumor mutation load levels compared with those in the low-risk group. The nomogram based on the risk score can distinguish the risk subtypes and individual prognosis of patients with OC. Additionally, M1 macrophages may be the critical target for immunotherapy in OC patients. Conclusion: With the in-depth analysis of the immune microenvironment of OC, the PRSM was constructed to predict the OC patient prognosis and identify the subgroup of the patients benefiting from immunotherapy.

Safety of Antiplatelet Therapy in Noncardioembolic Ischemic Stroke With Thrombocytopenia: The CASE II Study.

BACKGROUND: There is scant evidence regarding the safety of antiplatelet therapy in acute ischemic stroke (AIS) patients with thrombocytopenia. Our study aims to address this concern by examining AIS patients with thrombocytopenia from a large database in real-world settings. METHODS AND RESULTS: We included patients with AIS with a platelet count <100×109/L who had complete records of antiplatelet drug use. Those requiring anticoagulation or having contraindications to antiplatelet therapy were excluded. Short-term safety outcomes were in-hospital bleeding events, while the long-term safety outcome was 1-year all-cause mortality. A good clinical outcome was defined as functional independence, indicated by a modified Rankin Scale score of 0 to 2 at discharge. Propensity score matched analyses were used. We screened 169 423 patients with AIS from 90 stroke centers in the CASE II register, ultimately enrolling 2808 noncardioembolic patients with thrombocytopenia. In the propensity score matched analyses, no significant difference was observed between the antiplatelet and nonantiplatelet groups in terms of intracranial hemorrhage (odds ratio=0.855 [95% CI, 0.284-5.478]; P=0.160) or gastrointestinal bleeding (odds ratio=2.034 [95% CI, 0.755-5.478]; P=0.160). Antiplatelet therapy was associated with improved functional outcomes at discharge (odds ratio=1.405 [95% CI, 1.028-1.920]; P=0.033), and showed a trend towards reducing 1-year mortality (odds ratio=0.395 [95% CI, 0.152-1.031]; P=0.058). CONCLUSIONS: The use of antiplatelet therapy lessened as platelet count decreased in patients with AIS with thrombocytopenia. However, our findings suggest that antiplatelet medications remain safe and effective for this population.

Cancer survival analysis on population-based cancer registry data in Zhejiang Province, China (2018-2019).

Objective: This is a comprehensive overview of long-term cancer survival in Zhejiang Province, China. Hybrid analysis, a combination of cohort and period analysis, has been proposed to derive up-to-date cancer survival estimates. Using this approach, we aimed to timely and accurately analyze the 5-year relative survival (RS) and net survival (NS) in cancer registries of Zhejiang Province, China. Methods: A total of 255,725 new cancer cases diagnosed during 2013-2017 were included in 14 cancer registries in Zhejiang Province, China, with a follow-up on vital status until the end of 2019. The hybrid analysis was used to calculate the 5-year RS and 5-year NS during 2018-2019 for overall and stratifications by sex, cancer type, region, and age at diagnosis. Results: During 2018-2019, the age-standardized 5-year RS and NS for overall cancer in Zhejiang was 47.5% and 48.6%, respectively. The age-standardized 5-year RS for cancers of women (55.4%) was higher than that of men (40.0%), and the rate of urban areas (49.7%) was higher than that of rural areas (43.1%). The 5-year RS declined along with age, from 84.4% for ages <45 years to 23.7% for ages >74 years. Our results of the RS and NS showed the similar trend and no significant difference. The top five cancers with top age-standardized 5-year RS were thyroid cancer (96.0%), breast cancer (84.3%), testicular cancer (79.9%), prostate cancer (77.2%), and bladder cancer (70.6%), and the five cancers with the lowest age-standardized 5-year RS were pancreatic cancer (6.0%), liver cancer (15.6%), gallbladder cancer (17.1%), esophageal cancer (22.7%), and leukemia (31.0%). Conclusions: We reported the most up-to-date 5-year cancer RS and NS in Zhejiang Province, China for the first time, and found that the 5-year survival for cancer patients in Zhejiang during 2018-2019 was relatively high. The population-based cancer registries are recognized as key policy tools that can be used to evaluate both the impact of cancer prevention strategies and the effectiveness of health systems.

Preparation of molecularly imprinted polymer for the specific adsorption and selective extraction of alkylresorcinols from whole wheat flour.

Alkylresorcinols are important biomarkers for evaluating whole wheat foods. However, their structures encompass a broad spectrum of homologs, making isolating and analyzing individual alkylresorcinol notably challenging. Herein, we synthesized highly selective molecularly imprinted polymers (MIPs) utilizing a facile and cost-effective precipitation polymerization method and 5-heneicosylresorcinol (ARC21:0) as the template molecule. Various crucial preparation parameters were systematically optimized, such as different porogens, functional monomers, imprinting ratios, and polymerization time. The polymers were characterized through scanning electron microscopy and Fourier transform infrared spectroscopy, and their adsorption performances were thoroughly evaluated. MIPs exhibited a notably enhanced adsorption capacity compared with that of non-imprinted polymers, reaching an optimal adsorption amount of 71.75 mg·mL-1 and imprinting factor of 2.02. Altogether, the synthesized MIPs showed superior affinity and selectivity for ARC21:0, as confirmed by their selective extraction, suggesting their potential applications in the analysis, separation, and monitoring of ARC21:0 in whole wheat foods.

Molecularly Imprinted Electrochemical Sensor Based on α-Cyclodextrin Inclusion Complex and MXene Modification for Highly Sensitive and Selective Detection of Alkylresorcinols in Whole Wheat Foods.

Authenticating whole wheat foods poses a significant challenge for both the grain industry and consumers. Alkylresorcinols (ARs), serving as biomarkers of whole wheat, play a crucial role in assessing the authenticity of whole wheat foods. Herein, we introduce a novel molecularly imprinted electrochemical sensor with modifications involving a molecularly imprinted polymer (MIP) and MXene nanosheets, enabling highly sensitive and selective detection of ARs. Notably, we specifically chose 5-heneicosylresorcinol (AR21), the predominant homologue in whole wheat, as the template molecule. α-Cyclodextrin and acrylamide served as dual functional monomers, establishing a robust multiple interaction between the MIP and AR21. As a result, the sensor exhibited a wide linear range of 0.005 to 100 µg·mL-1 and a low detection limit of 2.52 ng·mL-1, demonstrating exceptional selectivity and stability. When applied to commercial whole wheat foods, the assay achieved satisfactory recoveries and accuracy, strongly validating the practicality and effectiveness of this analytical technique.

Association between metabolic syndrome severity score and cardiovascular disease: results from a longitudinal cohort study on Chinese adults.

Objective: This study aimed to quantify the severity of metabolic syndrome(MetS) and investigate its association with cardiovascular disease(CVD) risk on Chinese adults. Methods: 13,500 participants from the Zhejiang Adult Chronic Disease Study were followed up between 2010 and 2021. A continuous MetS severity score derived from the five components of MetS was used to quantify MetS severity, and the association between MetS severity and the risk of incident CVD was assessed using Cox proportional hazard and restricted cubic spline regression. Results: Both the presence and severity of MetS were strongly associated with CVD risk. MetS was related to an increased risk of CVD (hazard ratio(HR):1.700, 95% confidence interval(CI): 1.380-2.094). Compared with the hazard ratio for CVD in the lowest quartile of the MetS severity score, that in the second, third, and highest quartiles were 1.812 (1.329-2.470), 1.746 (1.265-2.410), and 2.817 (2.015-3.938), respectively. A linear and positive dose-response relationship was observed between the MetS severity and CVD risk (P for non-linearity = 0.437). Similar results were found in various sensitivity analyses. Conclusion: The MetS severity score was significantly associated with CVD risk. Assessing MetS severity and further ensuring intervention measures according to the different severities of MetS may be more useful in preventing CVD.

A Review of deep learning methods for denoising of medical low-dose CT images.

To prevent patients from being exposed to excess of radiation in CT imaging, the most common solution is to decrease the radiation dose by reducing the X-ray, and thus the quality of the resulting low-dose CT images (LDCT) is degraded, as evidenced by more noise and streaking artifacts. Therefore, it is important to maintain high quality CT image while effectively reducing radiation dose. In recent years, with the rapid development of deep learning technology, deep learning-based LDCT denoising methods have become quite popular because of their data-driven and high-performance features to achieve excellent denoising results. However, to our knowledge, no relevant article has so far comprehensively introduced and reviewed advanced deep learning denoising methods such as Transformer structures in LDCT denoising tasks. Therefore, based on the literatures related to LDCT image denoising published from year 2016-2023, and in particular from 2020 to 2023, this study presents a systematic survey of current situation, and challenges and future research directions in LDCT image denoising field. Four types of denoising networks are classified according to the network structure: CNN-based, Encoder-Decoder-based, GAN-based, and Transformer-based denoising networks, and each type of denoising network is described and summarized from the perspectives of structural features and denoising performances. Representative deep-learning denoising methods for LDCT are experimentally compared and analyzed. The study results show that CNN-based denoising methods capture image details efficiently through multi-level convolution operation, demonstrating superior denoising effects and adaptivity. Encoder-decoder networks with MSE loss, achieve outstanding results in objective metrics. GANs based methods, employing innovative generators and discriminators, obtain denoised images that exhibit perceptually a closeness to NDCT. Transformer-based methods have potential for improving denoising performances due to their powerful capability in capturing global information. Challenges and opportunities for deep learning based LDCT denoising are analyzed, and future directions are also presented.

Ambient PM2.5 and cardiopulmonary mortality in the oldest-old people in China: A national time-stratified case-crossover study.

BACKGROUND: Evidence on the associations of fine particulate matter (PM2.5) with cardiopulmonary mortality in the oldest-old (aged 80+ years) people remains limited. METHODS: We conducted a time-stratified case-crossover study of 1,475,459 deaths from cardiopulmonary diseases in China to estimate the associations between short-term exposure to ambient PM2.5 and cardiopulmonary mortality among the oldest-old people. FINDINGS: Each 10 µg/m3 increase in PM2.5 concentration (6-day moving average [lag05]) was associated with higher mortality from cardiopulmonary diseases (excess risks [ERs] = 1.69%, 95% confidence interval [CI]: 1.54%, 1.84%), cardiovascular diseases (ER = 1.72%, 95% CI: 1.54%, 1.90%), and respiratory diseases (ER = 1.62%, 95% CI: 1.33%, 1.91%). Compared to the other groups, females (ER = 1.94%, 95% CI: 1.73%, 2.15%) (p for difference test = 0.043) and those aged 95-99 years (ER = 2.31%, 95% CI: 1.61%, 3.02%) (aged 80-85 years old was the reference, p for difference test = 0.770) presented greater mortality risks. We found 14 specific cardiopulmonary causes associated with PM2.5, out of which emphysema (ER = 3.20%, 95% CI: 1.57%, 4.86%) had the largest association. Out of the total deaths, 6.27% (attributable fraction [AF], 95% CI: 5.72%, 6.82%) were ascribed to short-term PM2.5 exposure. CONCLUSIONS: This study provides evidence of PM2.5-induced cardiopulmonary mortality and calls for targeted prevention actions for the oldest-old people. FUNDING: This work was supported by the National Key Research and Development Program of China, the National Natural Science Foundation of China, the Foreign Expert Program of the Ministry of Science and Technology, the Natural Science Foundation of Guangdong, China, and the Science and Technology Program of Guangzhou.

Development and evaluation of a risk assessment tool for the personalized screening of breast cancer in Chinese populations: A prospective cohort study.

INTRODUCTION: Breast cancer is a significant contributor to female mortality, exerting a public health burden worldwide, especially in China, where risk-prediction models with good discriminating accuracy for breast cancer are still scarce. METHODS: A multicenter screening cohort study was conducted as part of the Cancer Screening Program in Urban China. Dwellers aged 40-74 years were recruited between 2014 and 2019 and prospectively followed up until June 30, 2021. The entire data set was divided by year of enrollment to develop a prediction model and validate it internally. Multivariate Cox regression was used to ascertain predictors and develop a risk-prediction model. Model performance at 1, 3, and 5 years was evaluated using the area under the curve, nomogram, and calibration curves and subsequently validated internally. The prediction model incorporates selected factors that are assigned appropriate weights to establish a risk-scoring algorithm. Guided by the risk score, participants were categorized into low-, medium-, and high-risk groups for breast cancer. The cutoff values were chosen using X-tile plots. Sensitivity analysis was conducted by categorizing breast cancer risk into the low- and high-risk groups. A decision curve analysis was used to assess the clinical utility of the model. RESULTS: Of the 70,520 women enrolled, 447 were diagnosed with breast cancer (median follow-up, 6.43 [interquartile range, 3.99-7.12] years). The final prediction model included age and education level (high, hazard ratio [HR], 2.01 [95% CI, 1.31-3.09]), menopausal age (≥50 years, 1.34 [1.03-1.75]), previous benign breast disease (1.42 [1.09-1.83]), and reproductive surgery (1.28 [0.97-1.69]). The 1-year area under the curve was 0.607 in the development set and 0.643 in the validation set. Moderate predictive discrimination and satisfactory calibration were observed for the validation set. The risk predictions demonstrated statistically significant differences between the low-, medium-, and high-risk groups (p < .001). Compared with the low-risk group, women in the high- and medium-risk groups posed a 2.17-fold and 1.62-fold elevated risk of breast cancer, respectively. Similar results were obtained in the sensitivity analyses. A web-based calculator was developed to estimate risk stratification for women. CONCLUSIONS: This study developed and internally validated a risk-adapted and user-friendly risk-prediction model by incorporating easily accessible variables and female factors. The personalized model demonstrated reliable calibration and moderate discriminative ability. Risk-stratified screening strategies contribute to precisely distinguishing high-risk individuals from asymptomatic individuals and prioritizing breast cancer screening. PLAIN LANGUAGE SUMMARY: Breast cancer remains a burden in China. To enhance breast cancer screening, we need to incorporate population stratification in screening. Accurate risk-prediction models for breast cancer remain scarce in China. We established and validated a risk-adapted and user-friendly risk-prediction model by incorporating routinely available variables along with female factors. Using this risk-stratified model helps accurately identify high-risk individuals, which is of significant importance when considering integrating individual risk assessments into mass screening programs for breast cancer. Current clinical breast cancer screening lacks a constructive clinical pathway and guiding recommendations. Our findings can better guide clinicians and health care providers.

Disease burden and risk factors of colorectal cancer in Zhejiang Province from 1990 to 2019 / 预防医学

Objective@#To analyze the disease burden and risk factors of colorectal cancer in Zhejiang Province from 1990 to 2019, so as to provide the basis for prevention and control of colorectal cancer.@*Methods@#Based on data of 2019 Global Burden of Disease (GDB 2019), disease burden and risk factors of colorectal cancer in Zhejiang Province from 1990 to 2019 was assessed using years of life lost (YLL), years lived with disability (YLD), disability-adjusted life years (DALY).@*Results@#In 2019, the YLL rate, YLD rate and DALY rate caused by colorectal cancer in Zhejiang Province were 496.15/105, 31.81/105 and 527.96/105, respectively. From 1990 to 2019, the YLL rate, YLD rate and DALY rate caused by colorectal cancer in Zhejiang Province increased by 114.90%, 482.60% and 123.38%, respectively, showing increasing trends (average annual percent change values were =2.663, 6.283 and 2.800, respectively,all P<0.05). From 1990 to 2019, the YLL rate, YLD rate and DALY rate in the age groups of 15 to 49 years, 50 to 69 years and 70 years and older showed increasing trends (all P<0.05). In 1990, the top ten risk factors for colorectal cancer in Zhejiang Province were diet low in calcium, diet low in milk, diet low in whole grains, smoking, alcohol use, low physical activity, high fasting plasma glucose, diet high in red meat, diet low in fiber and high body mass index. In 2019, the top ten risk factors for colorectal cancer in Zhejiang Province were diet low in milk, diet low in whole grains, diet low in calcium, alcohol use, diet high in red meat, high body mass index, high fasting plasma glucose, low physical activity, diet low in fiber and diet high in processed meat.@*Conclusions@#The disease burden of colorectal cancer in Zhejiang Province showed an upward trend from 1990 to 2019. The top ten risk factors for colorectal cancer remained between 1990 and 2019, while there was a slight change in ranking.

Associations between experience of stressful life events and cancer prevalence in China: results from the China Kadoorie Biobank study.

BACKGROUND: Studies examining the relationships of stressful life events and cancer yielded inconsistent findings, while relevant evidence in mainland China is scarce. The current study sought to determine whether experience of stressful life events was associated with cancer prevalence in Chinese population. METHODS: We used cross-sectional data from the China Kadoorie Biobank study which that recruited 0.5 million Chinese adults aged 30 to 79 from 2004 to 2008. Logistic regression models were used to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for cancer associated with stressful life events reported at baseline. RESULTS: Among the 461,696 participants included in this analysis, 2,122 (0.46%) had self-reported cancer with the mean (SD) age was 57.12 (9.71) years. Compared to those without any stressful life event, participants who experienced 1 and 2 or more events had significantly higher odds of cancer, with the ORs of 1.80 (95% CI: 1.58-2.05) and 3.05 (2.18-4.28). For categories of work-, family-, and personal-related events, the OR of cancer was 1.48 (1.07-2.05), 2.06 (1.80-2.35), and 1.65 (1.17-2.33), respectively. Regarding the specific stressful life events, loss of income/living on debt, major conflict within family, death/major illness of other close family member, and major injury/traffic accident were significantly associated with increased odds of cancer, with the ORs of 2.64 (1.81-3.86), 1.73 (1.20-2.50), 2.36 (2.05-2.72), and 2.11 (1.43-3.13). CONCLUSION: Our findings suggested that experiences of cumulative and specific stressful life events were significantly associated with increased cancer prevalence in Chinese population.

Analysis of the Risk Factors for Mechanical Allodynia in Herpetic Neuralgia: A Retrospective Cross-Sectional Study.

Purpose: Mechanical allodynia is reportedly common during herpetic neuralgia. The purpose of this study was to establish a risk prediction model to predict the individual risk of allodynia in herpetic neuralgia. Methods: Three hundred and eighty-six patients with trunk herpetic neuralgia were divided into two regions, T2-5 and T6-11. The causality between allodynia and other factors was analyzed by a binary logistic regression model. Results: 42.2% of subjects had allodynia, 137 suffered from dynamic allodynia, and 110 with dynamic allodynia experienced local sweating. The following 5 items as predictors determined this model: local sweating (Odd Ratio = 27.57, P<0.001), lesion location (Odd Ratio=2.46, P =0.017), pain intensity (Odd Ratio=1.38, P =0.020), pain duration (Odd Ratio=0.94, P =0.006), and local scars (Odd Ratio=0.07, P<0.001). The presence and development of allodynia are associated with local sweating. The positive proportion of the Iodine-starch test between the T2-5 (50.0%) with the T6-11 (23.7%) had a statistically significant difference (χ2=5.36, P=0.021). 29.5% of patients at the T2-6 had obvious sweating, which was different from only sticky feelings at the T6-11 (70.5%, χ2=10.88, P=0.001). 19.2% of patients with residual scars and allodynia was significantly lower than 48.5% of patients without allodynia (χ2=15.28, P<0.001). Conclusion: This analysis suggests that local sweating is a concomitant symptom in dynamic allodynia, which imply the sympathetic nerves innervating the sweat glands of the skin were also involved during herpetic neuralgia. This may assist in the evaluation of dynamic allodynia and prove the role of sympathetic nerve intervention for herpetic neuralgia.

Health and wellbeing among the empty nest and non-empty nest elderly in China-Results from a national cross-sectional study.

BACKGROUND: The number of empty nest elderly in China has gradually increased in recent years. There is growing concern about the physical and mental health of this population as empty nest elderly are commonly at the risk of compromising health, home safety and quality of life. This study reported the health and well-being of empty nest elderly with regards to their health status, depression and satisfaction, lifestyle as compared to non-empty nest elderly in China. METHODS: Data was collected from the 2018 follow-up interviews of China Health and Retirement Longitudinal Survey. We included 4,630 empty nest elderly and 6,188 non-empty nest elderly. Chi-square Test and Logistic Regression were used to compare the differences between these two groups. RESULTS: As compared to the non-empty nest elderly, there was higher proportion of empty nest elderly who suffered from dyslipidemia, diabetes, chronic lung diseases, heart attack (27.0% vs. 25.0%; 16.6% vs. 15.1%; 19.4% vs. 16.4%; 26.3% vs. 23.4%, P < 0.05). The empty nest elderly had higher proportion of participants who drank more than once a month (25.3% vs. 23.9%, P < 0.05), who felt satisfied with their marriage (71.6% vs. 66.2%, P < 0.001), who were satisfied with their children's relationship (85.2% vs. 83.2%, P < 0.001). However, these significances disappeared in the Logistic Regression analysis (P > 0.05). CONCLUSION: Our study showed that significant between-group difference was found between empty nest elderly and non-empty nest elderly in their health and wellbeing. However, disappearance of such difference in the multivariable analysis may indicate improved health and wellbeing among the empty nest elderly. Even though our study still suggested the importance of improving the health, lifestyles and family dynamics of the elderly and promoting the integration of health and social care for the elderly, especially among the empty nest elderly.

High-throughput sequencing reveals Jatrorrhizine inhibits colorectal cancer growth by ferroptosis-related genes.

BACKGROUND: Colorectal cancer is a malignant tumor that poses a serious threat to human health. The main objective of this study is to investigate the mechanism by which Jatrorrhizine (JAT), a root extract from Stephania Epigaea Lo, exerts its anticancer effects in colorectal cancer. METHODS: We initially assessed the inhibitory properties of JAT on SW480 cells using MTT and cell scratch assays. Flow cytometry was employed to detect cell apoptosis. Differentially expressed genes were identified through high-throughput sequencing, and they were subjected to functional enrichment and signaling pathway analysis and PPI network construction. RT-qPCR was used to evaluate gene expression and identify critical differentially expressed genes. Finally, the function and role of differentially expressed genes produced by JAT-treated SW480 cells in colorectal cancer will be further analyzed using the TCGA database. RESULTS: Our study demonstrated that JAT exhibits inhibitory effects on SW480 cells at concentrations of 12.5µM, 25µM, 50µM, and 75µM without inducing cell apoptosis. Through high-throughput sequencing, we identified 244 differentially expressed genes. KEGG and GO analysis of high-throughput sequencing results showed that differentially expressed genes were significantly enriched in MAPK, Wnt, and P53 signaling pathways. Notably, JAT significantly altered the expression of genes associated with ferroptosis. Subsequent RT-qPCR showed that the expression of ferroptosis genes SLC2A3 and ASNS was significantly lower in JAT-treated SW480 cells than in the control group. Analysis by TCGA data also showed that ferroptosis genes SLC2A3 and ASNS were significantly highly expressed in COAD. The prognosis of SLC2A3 was significantly worse in COAD compared to the normal group. SLC2A3 may be a core target of JAT for the treatment of COAD. CONCLUSIONS: JAT can inhibit COAD growth by ferroptosis-related genes. And it is a potential natural substance for the treatment of COAD.

The association of heatwave with drowning mortality in five provinces of China.

Drowning is a serious public health problem in the world. Several studies have found that ambient temperature is associated with drowning, but few have investigated the effect of heatwave on drowning. This study aimed to explore the associations between heatwave and drowning mortality, and further estimate the mortality burden of drowning attributed to heatwave in China. Drowning mortality data were collected in 71 prefectures in China during 2013-2018 from provincial vital register system. Meteorological data at the same period were collected from European Centre for Medium-Range Weather Forecasts (ECMWF). A distributed lag non-linear model (DLNM) was first to explore the association between heatwave and drowning mortality in each prefecture. Secondly, the prefecture-specific associations were pooled using meta-analysis. Finally, attributable fractions (AFs) of drowning deaths caused by heatwave were estimated. Compared to normal day, the mortality risk of drowning significantly increased during heatwave (RR = 1.20, 95%CI: 1.18-1.23). Higher risks were observed in males (RR = 1.23, 95%CI: 1.20-1.27) than females (RR = 1.18, 95%CI: 1.13-1.23), in children aged 5-14 years old (RR = 1.24, 95%CI: 1.15-1.33) than other age groups, in urban city (RR = 1.32, 95%CI: 1.28-1.36) than rural area (RR = 1.09, 95%CI: 1.07-1.12) and in Jilin province (RR = 2.85, 95%CI: 1.61-5.06) than other provinces. The AF of drowning deaths due to heatwave was 11.4 % (95%CI: 10.0 %-12.9 %) during heatwave and 1.0 % (95%CI: 0.9 %-1.1 %) during study period, respectively. Moreover, the AFs during study period were higher for male (1.2 %, 95%CI: 1.0 %-1.3 %), children 5-14 years (1.1 %, 95%CI: 0.7 %-1.6 %), urban city (1.6 %, 95%CI: 1.4 %-1.8 %) than their correspondents. These differences were also observed in AFs during heatwave. We found that heatwave may significantly increase the mortality risk of drowning mortality, and its mortality burden attributable to heatwave was noteworthy. Targeted intervention should be carried out to decrease drowning mortality during heatwave.

The Combined Effects of Short-Term Exposure to Multiple Meteorological Factors on Unintentional Drowning Mortality: Large Case-Crossover Study.

BACKGROUND: Drowning is a serious public health problem worldwide. Previous epidemiological studies on the association between meteorological factors and drowning mainly focused on individual weather factors, and the combined effect of mixed exposure to multiple meteorological factors on drowning is unclear. OBJECTIVE: We aimed to investigate the combined effects of multiple meteorological factors on unintentional drowning mortality in China and to identify the important meteorological factors contributing to drowning mortality. METHODS: Unintentional drowning death data (based on International Classification of Diseases, 10th Edition, codes W65-74) from January 1, 2013, to December 31, 2018, were collected from the Disease Surveillance Points System for Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces, China. Daily meteorological data, including daily mean temperature, relative humidity, sunlight duration, and rainfall in the same period were obtained from the Chinese Academy of Meteorological Science Data Center. We constructed a time-stratified case-crossover design and applied a generalized additive model to examine the effect of individual weather factors on drowning mortality, and then used quantile g-computation to estimate the joint effect of the mixed exposure to meteorological factors. RESULTS: A total of 46,179 drowning deaths were reported in the 5 provinces in China from 2013 to 2018. In an effect analysis of individual exposure, we observed a positive effect for sunlight duration, a negative effect for relative humidity, and U-shaped associations for temperature and rainfall with drowning mortality. In a joint effect analysis of the above 4 meteorological factors, a 2.99% (95% CI 0.26%-5.80%) increase in drowning mortality was observed per quartile rise in exposure mixture. For the total population, sunlight duration was the most important weather factor for drowning mortality, with a 93.1% positive contribution to the overall effects, while rainfall was mainly a negative factor for drowning deaths (90.5%) and temperature and relative humidity contributed 6.9% and -9.5% to the overall effects, respectively. CONCLUSIONS: This study found that mixed exposure to temperature, relative humidity, sunlight duration, and rainfall was positively associated with drowning mortality and that sunlight duration, rather than temperature, may be the most important meteorological factor for drowning mortality. These findings imply that it is necessary to incorporate sunshine hours and temperature into early warning systems for drowning prevention in the future.

Association of high miR-27a, miR-206, and miR-214 expression with poor patient prognosis and increased chemoresistance in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype, associated with early metastasis and recurrence as well as poor patient outcome. TNBC does not or weakly respond to hormonal or HER2-targeted therapies. Therefore, there is a strong need to identify other potential molecular targets for TNBC therapy. Micro-RNAs play important roles in the post-transcriptional regulation of gene expression. Thus, micro-RNAs, displaying an association between elevated expression and poor patient prognosis, may represent candidates for such novel tumor targets. In the present study, we evaluated the prognostic impact of miR-27a, miR-206, and miR-214 in TNBC via qPCR in tumor tissue (n=146). In univariate Cox regression analysis, elevated expression of all three analyzed micro-RNAs was significantly associated with shortened disease-free survival (hazard ratio [HR] for miR-27a: 1.85, P=0.038; miR-206: 1.83, P=0.041; miR-214: 2.06, P=0.012). In multivariable analysis, the micro-RNAs remained independent biomarkers for disease-free survival (HR for miR-27a: 1.99, P=0.033; miR-206: 2.14, P=0.018; miR-214: 2.01, P=0.026). Furthermore, our results suggest that elevated levels of these micro-RNAs are linked to enhanced resistance to chemotherapy. Based on the association of high expression levels with shortened patient survival and increased chemoresistance, miR-27a, miR-206, and miR-214 may represent novel molecular targets for TNBC.